Field of the Invention
This invention relates generally to a system and method for adapting a speech recognition vocabulary and, more particularly, to a system and method for adding a dictionary adaptation module to a speech recognition and generation engine or system that analyzes dialog and suggests words that may be added to a dictionary of the speech recognition and generation engine or system.
Discussion of the Related Art
Speech recognition systems enable microphone-equipped computing devices to interpret speech and thereby provide an alternative to conventional human-to-computer input devices such as keyboards or keypads. A typical speech recognition system includes a microphone and an acoustic interface that receives a user's speech and digitizes it into acoustic data. Also included, for example, is an acoustic pre-processor that parses the acoustic data into information with acoustic features and a decoder that uses acoustic models to decode the acoustic features and generate at least one hypotheses, which can include decision logic to select a best hypothesis of subwords and words corresponding to the user's speech.
Speech recognition systems for natural utterances typically use fixed word dictionaries. The size of the dictionary has an immediate effect on the accuracy and speed of speech recognition, where small dictionaries reduce confusion among words and require less resources, such as CPU and memory, and large dictionaries have good coverage of the language such that many words may be considered for any utterance.
Some known approaches to dictionary definitions include narrow sets of predefined messages, such as canned messages, small dictionaries and large dictionaries. With small dictionaries, for example, 1,000 or less words, many words are outside of the dictionary and thus cannot be recognized, i.e., many words are Out Of Vocabulary (OOV). With large dictionaries, for example, 20,000 or more words, there is a higher probability that the spoken words are found in the dictionary and thus are recognizable. However, there is also a higher probability of word confusion with large dictionaries. Thus, there is a need in the art for a dictionary adaptation module for a speech recognition and generation engine that allows for a balance between maintaining a small dictionary and preventing OOV by achieving a reasonable coverage of the expected word that is uttered.